AI-Driven Security Protection for Public Security Services: Risk Identification and Mitigation

Yulei Lu

doi:10.47297/taposatWSP2633-456907.20250612

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AI-Driven Security Protection for Public Security Services: Risk Identification and Mitigation

Volume 6, Issue 12

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AI-Driven Security Protection for Public Security Services: Risk Identification and Mitigation
AI-Driven Security Protection for Public Security Services: Risk Identification and Mitigation
Graduate student of Zhejiang Police College, Haiyan County Public Security Bureau, Jiaxing, Zhejiang, 314300, China
Vol. 6, Issue 12, Pages: 30-34(2025)
Published：30 December 2025
DOI：10.47297/taposatWSP2633-456907.20250612
Accepted：

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Lu Yulei.AI-Driven Security Protection for Public Security Services: Risk Identification and Mitigation[J].Theory and Practice of Science and Technology,2025,06(12):30-34.
DOI：

Lu Yulei.AI-Driven Security Protection for Public Security Services: Risk Identification and Mitigation[J].Theory and Practice of Science and Technology,2025,06(12):30-34. DOI： 10.47297/taposatWSP2633-456907.20250612.

摘要

Abstract

With the deep integration of artificial intelligence (AI) into public security work

public security organs across China have actively explored the application of large AI model technologies to develop intelligent infrastructure including training datasets

knowledge bases

and public security-specific large models

injecting technological momentum into the continuous enhancement of the new-type combat capabilities of public security organs. However

in the process of improving policing efficiency

issues such as data security breaches

algorithmic bias

and adversarial attacks have occurred frequently. The problem of black-box algorithms has aroused widespread public concern

and ensuring the safety

reliability

and controllability of AI has become a prominent issue

which is increasingly threatening national security. This study systematically analyzes various security risks in AI-driven public security services

and proposes responsive strategies to strengthen confidential security management and data security protection from the perspectives of ideological risks

policy and legal norms

technical construction risks

and regulatory governance mechanisms. It provides insights for public security organs at all levels to seize the opportunities of AI empowerment while using AI technologies in a safe manner.

关键词

Keywords

references

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